The Use of Computerized Simulations to Promote Self Management Behaviors in Individuals with Type 2 Diabetes Location: HSEB 5100C Type II Diabetes (T2DM) is a chronic progressive endocrine disorder affecting millions of Americans. Effective self-management of T2DM requires the regular performance of specific behaviors. In this research we focused on the promotion of physical activity since it is highly efficacious and the least performed of diabetes self-management behaviors This dissertation describes a line of research that addresses basic questions related to the use of computerized simulation to affect the knowledge, beliefs, motivation and self-management behaviors of individuals with type 2 diabetes (T2DM). We first describe a conceptual framework for the design of self-management software applications. This framework highlights functions of prior self-management applications that have demonstrated efficacy and provides recommendations drawn from the psychology literature to further improve the efficacy of self-management applications. The design of an envisioned diabetes self-management application is described as an exemplar. The subsequent chapters describe tests of research questions related to this envisioned intervention. We then describe the development and preliminary evaluation of the interface for the intervention described above. The derivation of simulated glucose curves for individuals with T2DM is described. Next we describe the formative evaluation of a paper-based prototype based on those curves. We then describe a randomized experiment of a narrated simulation based on simulated glucose curves. This trial tested the question: can computerized simulations affect the beliefs and behaviors of individuals with T2DM? In this experiment participant's beliefs changed in accordance with the presented evidence and the completion of a planning intervention resulted in significantly greater increase in physical activity. We then describe a test of the question: can predictive models of the acute physiologic effects of behavior be individualized? This study compared different predictive modeling techniques and found that a mixed effects modeling approach does improve in accuracy as the individual contributes more data. The implications of the results of this study for personalized consumer informatics interventions, with our intervention as an example, are discussed. The conclusion of this thesis is a discussion of the strengths and limitations of the work presented and the next steps in this line of research. Bryan Gibson is a PhD Candidate in the Department of Biomedical Informatics at the University of Utah. He received his Doctorate in Physical Therapy from the University of Utah in 2006. His research interests center on the use of evidence-based psychological models in the design of consumer health informatics interventions. Specifically, he is interested in the use of simulation to facilitate effective self-management of diabetes.
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Date: Dec. 16, 2011
Time: 1:00 pmSupervisory Committee: Charlene Weir, PhD; Jason Jones, PhD; Robin Marcus, PhD; Matthew Samore, MD; Nancy Staggers, RN, PhD
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